Compiler Optimization
IBM's latest Enterprise COBOL
V6.2, Automatic Binary Optimizer (ABO) V1.3 and Enterprise
PL/I V5.2 ship with advanced
optimization technology.
They have the capability to
generate code that can take
full advantage of the new z14
processor-especially the Vector
Packed Decimal Facility feature-to provide a significant
performance boost for business-critical COBOL and PL/I
applications. Enterprise COBOL
V6.2 and Enterprise PL/I V5.2
provide native support for JSON
objects, significantly increasing
the efficiency of exchanging
JSON data between applications
or through RESTful APIs.
IBM ABO is a unique offering with innovative technology
designed to optimize the performance of COBOL program
modules built with VS COBOL
II V1.3 to Enterprise COBOL for
z/OS V4.2, without the need for
recompiling from program source
(see Figure 1, page 18).
It uses an advanced optimization framework shipped in IBM
Enterprise COBOL for z/OS to
perform high-fidelity optimization
and generate code to fully exploit
IBM Z mainframes without affecting program logic. As a result,
the optimized modules run faster
but program behavior remains
unchanged, significantly reducing
testing effort.
Improving Application
Delivery Velocity
In today's era of digital transformation, it's imperative for enterprises
to drive faster innovation while
ensuring the stability of core business systems. For example:
*
If a new mobile app needs a
critical change to a back-end
transactional system, that
system of record must be
*
*
agile enough to provide those services in a
timely manner
You may have valuable z/OS business logic that
you want to expose as RESTful APIs for participation in the API economy
You want to recompile or optimize COBOL
and PL/I applications to get the most out of
your IBM Z hardware, and
need tools that can handle
the application migration,
deployment and operations
All of these activities require
modern DevOps tools for
The Benefits of Running
Machine Learning on z/OS
Thursday, November 16 | 10 PT / Noon CT / 1 ET
As businesses advance into the realm
of machine learning to enhance their
enterprise processing, the options for
how to implement it, where to run it,
and how to gain the most value can be
perplexing. Should data be collected
in a data lake? Should ML run in the
cloud? Is it better to put together your
own solution, or invest in a vendor's
solution?
FEATURING:
Emily Farmer
Senior Competitive Analyst
IBM
In this webinar presented by the IBM
CPO, we'll examine many of the factors that come into play when considering where and how to implement
machine learning and run the numbers to demonstrate the overall benefits of IBM Machine Learning on z/OS.
Register Today: webcasts.com/ibmsystemsmag
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ibmsystemsmag.com NOVEMBER/DECEMBER 2017 // 17

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